Surgical procedures which exert pressure on tissues and organs, or alter their composition, can tend to produce deformation of tissue. For example, deformation of brain tissue may occur when a craniotomy is opened and pressure on the brain is relieved, when a surgical device such as a surgical port or catheter is introduced into the brain, or when tissue is removed during surgery such as in a tumour resection. Deformation of tissue and its effects on the accuracy and precision of surgical procedures is an ongoing area of investigation and research, and there is a need for effective means to detect such deformation for surgical planning, navigation, and analysis. While much of the following discussion uses surgical procedures in the brain as examples, similar issues arise in surgery to the spine and other orthopedic applications and the techniques are generally applicable.
The complexities associated with tissue shifts that occur during surgery are not well addressed by currently available systems and methods. For example during a craniotomy, when a large portion of the skull of a patient is removed to allow for access to the brain, the brain tends to swell outside of the remaining skull that is encasing the brain due to a pressure differential between the brain and the operating room. This brain swelling, and brain sag due to gravity, can tend to lead to a significant shift in the brain tissue, often on the order of 1-2 cm. Additionally, as a tumor is resected from the brain the position of the remaining tissue tends to shift relative to the pre-operative images as a result of the decreased volume. These mechanisms of brain swelling, sag, and shift can result in significant variations between pre and intra operative brain position. There is therefore a need for effective means to detect tissue deformation resulting from various causes including tissue resection, swelling, and surgical tool insertions, to allow for improved surgical planning, navigation, and analysis.
Deformations of the brain tissues occur in the course of surgery because of physical and physiological phenomena. As a consequence of this brain-shift, images acquired preoperatively no longer correspond to the positioning of brain tissue. For this reason, any preoperative based neuro-navigation planning is compromised by intraoperative brain deformations. According to Buick et al [Bio-Mechanical Model of the Brain for a Per-Operative Image-Guided Neuronavigator Compensating for “Brain-Shift” Deformations], mathematical computer simulation models such as continuous mechanical linear and small deformations model may be used to model surgical interactions (i.e., tissue resection) in an interactive way.
Different tissue types possess different deformation properties, so current methods of detecting tissue deformation often segment the body into a variety of tissue types. For example, with respect to deformation with brain surgery, brain tissue tends to be analyzed based on tissue type such as grey matter, white matter and cerebrospinal fluid. These methods provide deformation models based on the distortion properties for each type of tissue. However, these current methods do not adjust the model based on knowledge of oriented tissue structure (such as nerve or muscle fiber direction) or connectivity of the underlying structure. Rather, these systems and methods tend to treat all similar tissue types homogenously. Hence there is a need for a system and method of detecting tissue deformation based on knowledge of oriented tissue structure or connectivity of the underlying structure, rather than simply tissue type. Furthermore, if the device being introduced to the tissue is geometrically of similar shape and size to its ingress and sufficiently rigid, the device will tend to constrain movement of tissue and will maintain an interface with the tissue of known position and shape, and so is significant to the equilibrium positioning of tissue.